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20202023
most citedSentinel-1 Additive Noise Removal from Cross-Polarization Extra-Wide TOPSAR with Dynamic Least-Squares

12 citations · 12 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023

Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation

Jun Zhou, Kai Chen, Linlin Xu +2

One critical challenge in 6D object pose estimation from a single RGBD image is efficient integration of two different modalities, i.e., color and depth. In this work, we tackle th…

cs.CV2023

Dynamic Clustering Transformer Network for Point Cloud Segmentation

Dening Lu, Jun Zhou, Kyle Yilin Gao +4

Point cloud segmentation is one of the most important tasks in computer vision with widespread scientific, industrial, and commercial applications. The research thereof has resulte…

cs.CV2022

3DCTN: 3D Convolution-Transformer Network for Point Cloud Classification

Dening Lu, Qian Xie, Linlin Xu +1

Although accurate and fast point cloud classification is a fundamental task in 3D applications, it is difficult to achieve this purpose due to the irregularity and disorder of poin…

cs.CV2021

The impact of data volume on performance of deep learning based building rooftop extraction using very high spatial resolution aerial images

Hongjie He, Ke Yang, Yuwei Cai +15

Building rooftop data are of importance in several urban applications and in natural disaster management. In contrast to traditional surveying and mapping, by using high spatial re…

cs.CV2020

DML-GANR: Deep Metric Learning With Generative Adversarial Network Regularization for High Spatial Resolution Remote Sensing Image Retrieval

Yun Cao, Yuebin Wang, Junhuan Peng +4

With a small number of labeled samples for training, it can save considerable manpower and material resources, especially when the amount of high spatial resolution remote sensing…

cs.CV2020

Quantization in Relative Gradient Angle Domain For Building Polygon Estimation

Yuhao Chen, Yifan Wu, Linlin Xu +1

Building footprint extraction in remote sensing data benefits many important applications, such as urban planning and population estimation. Recently, rapid development of Convolut…